Improving the Question Answering Quality using Answer Candidate Filtering based on Natural-Language Features-Reference-Cited by-同舟云学术

Improving the Question Answering Quality using Answer Candidate Filtering based on Natural-Language Features

Published:2021-11-26 Issue: Volume: Page:
ISSN:
Container-title:2021 16th International Conference on Intelligent Systems and Knowledge Engineering (ISKE)
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Author:

Gashkov Aleksandr¹,Perevalov Aleksandr²,Eltsova Maria³,Both Andreas¹

Affiliation:

1. Humanitarian Faculty Perm National Research Polytechnic University,Perm,Russia

2. Computer Science and Languages Anhalt University of Applied Sciences,Köthen (Anhalt),Germany

3. Technology Innovation Unit DATEV eG,Nuremberg,Germany

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9755300/9755317/09755382.pdf?arnumber=9755382

Reference38 articles.

1. The 2020 bilingual, bi-directional WebNLG+ shared task overview and evaluation results (WebNLG+ 2020);ferreira;Proceedings of the 3rd International Workshop on Natural Language Generation from the Semantic Web (WebNLG+),2020

2. A Holistic Natural Language Generation Framework for the Semantic Web

3. RuBQ: A Russian Dataset for Question Answering over Wikidata

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